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. 2024 Feb 12:55:63-73.
doi: 10.1016/j.athplu.2024.02.001. eCollection 2024 Mar.

Refined metabolite profiling in the collateral circulation of chronic total occlusion of coronary arteries: Insights from a metabolomics investigation

Hu Sigan  1 , Li Min  1 , Cheng Zengwei  1 , Gao Shiyi  1 , Kang Pinfang  1 , Gao Dasheng  1
Affiliations

Refined metabolite profiling in the collateral circulation of chronic total occlusion of coronary arteries: Insights from a metabolomics investigation

Hu Sigan et al. Atheroscler Plus. .

Abstract

Background and aims: To investigate the disparities in coronary collateral circulation (CCC) and peripheral serum metabolites among patients presenting with chronic total occlusion (CTO) of the coronary arteries, a non-targeted metabolic approach was employed.

Methods: A cohort of 22 patients diagnosed with CTO of coronary arteries in the context of coronary heart disease (CHD) was selected for blood sample collection from CCC and peripheral arteries. The patients were categorized into two groups, namely CTO-C and CTO-P. The Waters UPLC I-Class Plus is combined with the Q Exactive high-resolution mass spectrometer for metabolite separation and detection. The acquired raw data from mass spectrometry is subsequently imported into Compound Discoverer 3.2 software for comprehensive analysis, which seamlessly integrates the BGI Metabolome Database (BMDB), mzCloud database, and ChemSpider online database. Subsequently, the identified differential metabolites were subjected to a metabolic pathway enrichment analysis, as documented in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Results: A total of 403 differential metabolites were identified in CCC and peripheral serum samples from patients with CTO of coronary arteries in CHD. Compared to the CTO-P group, the CTO-C group exhibited decreased levels of metabolites such as Testosterone, dehydroepiandrosterone (DHA), deoxyacetone, while demonstrating increased levels of metabolites including Progesterone, androstanone, l-threonine. The biosynthesis pathway of steroid hormones emerges as the key metabolic pathway significantly associated with differential metabolites.

Conclusions: Through metabolomics analysis, distinct differences in the CCC and peripheral serum metabolites have been identified among patients with CTO of coronary artery. Notably, a significant association between the steroid hormone biosynthesis pathway and CCC has been observed.

Keywords: Collateral circulation; Coronary heart disease; Differential metabolites; Metabolic pathway; Non-targeted metabolomics.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Illustrates a CTO lesion in the left anterior descending artery, with the advancement of a guidewire and microcatheter through the CTO segment to obstruct antegrade blood flow. Using a microcatheter, blood samples were meticulously extracted from the collateral circulation of the right coronary artery, which retrogradely supplies blood to the left anterior descending branch. The arrow indicates the site of blood withdrawal.
Fig. 2
Fig. 2
a. Shows the base peak chromatogram (BPC) in positive ion mode for quality control, b. Shows the BPC in negative ion mode for quality control, c. Shows the BPC of two sample groups in positive ion mode, d. Shows the BPC of two sample groups in negative ion mode.
Fig. 2
Fig. 2
a. Shows the base peak chromatogram (BPC) in positive ion mode for quality control, b. Shows the BPC in negative ion mode for quality control, c. Shows the BPC of two sample groups in positive ion mode, d. Shows the BPC of two sample groups in negative ion mode.
Fig. 3
Fig. 3
a. Quality control PCA analysis model score plot, b. PCA analysis score plot of two groups, c. Score plot of PLS-DA analysis models for two groups, d. Score plot of OPLS-DA analysis models for two groups.
Fig. 4
Fig. 4
Replacement test chart of OPLS-DA analysis model. In Fig. 4, the R value is (0.0, 0.53) and the Q2 value is (0.0, −0.34). The red dotted line inclined upward and the intercept between Q2 and the longitudinal axis is less than 0, it indicates that the model is good and has not been fitted.
Fig. 5
Fig. 5
a. KEEG pathway donut chart, b. KEEG pathway bar chart.
Fig. 6
Fig. 6
a. Volcano plot, b. Bar plot.
Fig. 7
Fig. 7
a. Enrichment analysis-bubble diagram, b. Enrichment analysis abundance score plot of metabolic pathways, c. The network diagram of metabolic pathway enrichment analysis, d. ROC analysis-ROC plot.
Fig. 7
Fig. 7
a. Enrichment analysis-bubble diagram, b. Enrichment analysis abundance score plot of metabolic pathways, c. The network diagram of metabolic pathway enrichment analysis, d. ROC analysis-ROC plot.
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